History of Depression Increases Risk of Type 2 Diabetes in Younger Adults
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to assess the history of previous depression in people with incident diabetes compared with people without diabetes. RESEARCH DESIGN AND METHODS: We conducted a population-based nested case-control study using the administrative databases of Saskatchewan Health to assess the study objective. We identified cases of type 2 diabetes based on diagnostics codes and prescription records for individuals over the age of 20 years. For each case subject, two control subjects were randomly selected from the nondiabetic population during the same index year. History of depression, based on diagnostic codes and antidepressant prescription, was ascertained up to 3 years before index date. Simple and multivariate logistic regression analysis was used to estimate the odds ratio (OR) and 95% CIs, after adjusting for age, sex, and frequency of physician visits. RESULTS: Individuals with newly diagnosed diabetes (1,622 of 33,257; 4.9%) were 30% more likely to have had a previous history of depression compared with people without diabetes (2,279 of 59,420; 3.8%). This increased risk remained after controlling for sex and number of physician visits but was limited to subjects 20-50 years of age (adjusted OR 1.23 [95% CI 1.10-1.37]) and not in those aged > or =51 years (0.92 [0.84-1.00]). CONCLUSIONS: Depression appears to increase the risk of developing diabetes by approximately 23% in younger adults. This provides information regarding the temporality of the relationship between diabetes and depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".